In a main area of application of the present method, the area of digital subtraction angiography, blood vessels of the human body are recorded with an imaging system, in this case an X-ray system, and displayed. With this method series of X-ray images of the area under examination of interest for the patient are recorded while a contrast means is injected to highlight the vessels (filling images). Furthermore an image of the area under investigation is recorded without injecting a contrast means (mask image). By digitally subtracting the mask image from the relevant filling images, subtraction images are obtained on which only the vessels are visible while overlays from other X-ray-absorbing structures, such as for example bones, disappear because of the subtraction.
The subtraction of the images however requires these images to be recorded under the same geometrical conditions so that they cover the same area. As a result of motion of the recorded structures between the individual recordings the result can be disruptive motion artifacts in the subtracted images. These can be caused by the patient moving between the recording of the mask image and the recordings of the filling images. A consequence of these movements can be that the resulting subtraction image can no longer be used for the diagnosis. Thus it can occur in practice that, because of these types of motion artifacts, disrupted subtraction images have to be repeated. This often involves additional effort in time and contrast means as well as exposing the patient to additional radiation.
A method known as roadmapping is a technique associated with digital subtraction angiography. This technique is applied for selective categorization of vessels in interventional therapy. With such vessels the current position of an X-ray-absorbing catheter is shown by X-ray fluoroscopy in a two-dimensional image. To also enable the blood vessel to be recognized as what is known as a roadmap an image is recorded at the start of the intervention for which a small amount of contrast means has been injected. This image is retained as a mask image. The following fluoroscopy images obtained without injection of a contrast means are subtracted from the mask image in each case. In this way subtraction images are obtained on which the catheter is visible as a bright object against the dark blood vessel and the background has been eliminated by subtraction.
Like digital subtraction angiography, roadmapping is also disrupted in the same way by motion of the imaged structures during recording of a series of images. For motion between the recording of the mask image and the relevant fluoroscopy image two problems arise here however. One is that the back-ground is no longer correctly subtracted so that image artifacts occur. The other is that it can occur that the position determined by the image of the catheter relative to the blood vessel shown is not correct. This serious error can for example result in the image showing a catheter outside the vessel although it is actually located inside the vessel. In an extreme case such incorrect representations can lead to errors in catheter control and result in injuries to the vessel. If the patient moves during the intervention it is therefore frequently necessary for the roadmap to be refreshed by recording a new mask image. This requires additional time and uses up more contrast means and is associated with a higher dose of radiation for the patient.
Different solutions are currently known for avoiding or for reducing this problem. The following three types of approach to solutions can thus be identified.
Patient-linked solutions aim to avoid movement of the patient during image recording. Thus for example, during thorax examinations, the patient can be trained to hold their breath while the series of images is being recorded. A further option is to avoid a number of sources of motion artifacts by full anesthetic. A disadvantage of patient-linked methods lies in the fact that they are only partly effective or can-not always be used. A full anesthetic for example involves many risks and is thus not medically advised for many applications of digital subtraction angiography. In addition, even with a full anesthetic, a number of sources of motion artifacts, such as breath movement, are still present.
For the solutions which are linked to how the images are recorded the image recording is executed so that motion artifacts are minimized. Previously the main method known in this area has been the Gating method in which the recording is coupled with a physiological measurement. Thus for example with ECG Gating images of only acquired in a particular heart phase, to compensate for heart movements. Gating methods are however only usable for a few specific applications and can only avoid motion artifacts caused by specific sources for which physiological signals can be measured.
A further approach to a solution for avoiding motion artifacts consists of retrospective image processing of the recorded images. With these techniques the aim is to use image processing to obtain a better match between mask image and filling image. The simplest technique used is known as pixel shifting or subpixel shifting, in which the user shifts the mask image in relation to the filling image manually in two dimensions until a minimization of the motion artifacts is obtained in the subtraction image. This method is implemented in all commercial angiography systems. Automatic methods which define the best match on the basis of quantifiable similarity measures are present in a few commercial angiography systems. More complex methods do not use global pixel shifting over the entire area of the image but optimize local areas of the image separately from one another, as described for example in U.S. Pat. No. 4,870,692 A. Furthermore scientific literature proposes numerous more expensive methods for movement correction. These essentially involve optimization methods in which attempts are made to find the transformation between masking image and a filling image which results in the fewest motion artifacts. Further examples of retrospective image processing can be found in the publications “Motion compensated digital subtraction angiography”, M. Hemmendorff et al., SPIE '99, San Diego USA, Proceedings of play International Symposium on Medical Imaging 1999, Volume 3661, Image Processing, February 1999; Meijering E. H. et al., “Reduction of patient motion artifacts in digital subtraction angiography: evaluation of a fast and fully automatic technique”, Radiology, 2001 April; 219(1): 288-293; or “Retrospective Motion Correction in Digital Subtraction Angiography: A Review”, Erik H. W. Meijering et al., IEEE Transactions on Medical Imaging, Vol. 18, No. 1, January 1999, pp. 2-21.